pins
pins keeps adding a storage backend per release while retiring its original API
Comparison · Analytics
scales vs themis
A side-by-side editorial comparison of scales and themis — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r
scales vs themis: at a glance
What is scales?
scales keeps widening what ggplot2 can put on an axis.
scales supplies the breaks, labels and transformations behind ggplot2's axes and legends. Unlike much of the tidyverse infrastructure around it, it still ships genuine feature work each release: native timespan handling in 1.3.0, then custom range-training classes and label_glue() in 1.4.0.
What is themis?
themis is back to adding real resampling algorithms after a documentation-heavy stretch.
themis supplies recipes steps for handling class imbalance in tidymodels. The 1.0.x line was consumed by documentation accuracy, message translation and internal consistency work. Version 1.1.0 returns to substance with two new under-sampling methods.
scales vs themis: editorial side-by-side
scales
0.0ANALYTICS
scales keeps widening what ggplot2 can put on an axis.
◆ Current state
scales supplies the breaks, labels and transformations behind ggplot2's axes and legends. Unlike much of the tidyverse infrastructure around it, it still ships genuine feature work each release: native timespan handling in 1.3.0, then custom range-training classes and label_glue() in 1.4.0.
◆ Where it's heading
The arc runs toward extensibility and type coverage. First came built-in support for awkward types like difftime and hms; 1.4.0 inverts that by letting any third-party class participate in range training simply by implementing range() or levels(). Labelling is getting more expressive rather than merely more numerous.
◆ Prediction
Expect continued type-support and labelling work, with extension points that let downstream packages plug in their own classes instead of scales enumerating every one.
themis
2.5ANALYTICS
themis is back to adding real resampling algorithms after a documentation-heavy stretch.
◆ Current state
themis supplies recipes steps for handling class imbalance in tidymodels. The 1.0.x line was consumed by documentation accuracy, message translation and internal consistency work. Version 1.1.0 returns to substance with two new under-sampling methods.
◆ Where it's heading
The package grows by adding algorithms rather than restructuring itself. tomek() was rewritten to handle multiple classes and drop the unbalanced dependency, case weights arrived at 1.0.0, and cluster-centroid and condensed-nearest-neighbour under-sampling arrive now — each shipped as both a recipes step and a direct-implementation function.
◆ Prediction
Expect further under- and over-sampling methods in the same paired form, as the package fills out coverage of the standard class-imbalance literature.
Alternatives to scales and themis
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either scales or themis.
tsibble
tsibble shipped one release in five and a half years - the data structure is finished
yardstick
yardstick made fairness metrics a first-class part of tidymodels evaluation
tune
tune extends tuning past the model itself to postprocessors, and adds a second parallel backend
leaflet
leaflet relicensed to MIT and finished migrating off R's retired spatial stack
ggpubr
ggpubr reached 1.0.0 with p-value formatting presets for specific journals
See all scales alternatives → · See all themis alternatives →
Recent activity from scales and themis
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 10d agothemisthemis 1.1.0 adds cluster-centroid and CNN under-sampling
- 1y agoscalesscales 1.4.0 opens range training to custom classes
- 1y agothemisthemis 1.0.3 corrects resampling direction in documentation
- 2y agoscalesscales 1.3.0 makes timespans first-class on axes
- 2y agothemisthemis 1.0.2 makes internal consistency and speed changes
- 3y agothemisthemis 1.0.1 fixes upsampling errors when none is needed
- 3y agoscalesscales 1.2.1 re-documents to fix .Rd HTML issues
- 4y agothemisthemis 1.0.0 adds case weights to up- and down-sampling
- 4y agothemisthemis 0.2.2 rewrites tomek() for multiclass, drops a dependency
- 4y agoscalesscales 1.2.0 fixes currency sign order and adds scale_cut
- 6y agoscalesscales 1.1.1 fixes palette inversion and adds oob_keep()
- 6y agoscalesscales 1.1.0 reorganises breaks and labels into a naming scheme
Frequently asked questions
What is the difference between scales and themis?
Both compete on the same themes — r — within Analytics. themis is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is scales better than themis?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. themis is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to scales?
Top scales alternatives in Analytics are ranked by recent ship velocity. Browse the "scales alternatives" section above for the current picks, or visit /alternatives/scales-r for the full list with editorial commentary on each.
What are the best alternatives to themis?
Top themis alternatives in Analytics are ranked by recent ship velocity. Browse the "themis alternatives" section above for the current picks, or visit /alternatives/themis for the full list with editorial commentary on each.